Archive for October, 2009

So, when I read that the Baltimore Orioles were not going to pick upMelvin Mora‘s $8 million option I thought I’d check out whether or not this was a good decision. I didn’t even have to run the calculations to see that he’s not worth his option. And given his age, he may be done. But, it was his age that caught me off guard. I haven’t followed his career closely, and I had not realized how old he is.

He didn’t make it to the majors until age 27; and once he made it, he wasn’t all that spectacular. But, at 31, he batted .317/.418/.503—his first season with an OPS over .750. From 31–33 he averaged .312/.391/.513. Since then, he’s been a 750 OPS player. It’s an odd career shape—I wouldn’t advise projecting such a large mid-career bump—but it’s not unexpected that someone has a career like this.

What amazes me most is that he was allowed to stick around long enough to have his excellent years from 31–33. In most cases, teams give up on players in their late 20s who are past the development stage. But, for whatever reason, the O’s stuck by him and it paid off. His career path reminds me a little of Matt Diaz, who arrived later than most prospects, but has had a nice career since.

I believe that these types of players are underused by teams. Rather than waiting for a guy to bloom, teams (and players) just give up. But peak age for players is in the 29–30 range—not 27, as is often claimed—so many player leave the game before their time is up. Why not keep a few veterans at Triple-A, maybe even pay them a little more just to hang around? If one does blossom, he’s reserved and cheap through his peak.

Between the bad calls made during the MLB’s playoff and SEC football games, officiating has been a popular subject among my friends these days. This has gotten me thinking about umpires. Baseball cannot survive without human umpires; the game requires that snap judgments be made in real time. While replay could be used in spots, I feel that replay won’t fix the human problems that remain. I think fans would prefer that humans got the calls right in the first place so we wouldn’t have to wait for replay corrections.

In general, I think the umpires do a fine job, as I often find my initial disagreements to calls to be wrong after seeing the replay. Training and experience are going to make umpires better referees of play than fans, but that doesn’t mean that umpiring couldn’t be better. So, I decided to do a little exploratory data analysis to see if there is anything we can learn about the state of umpiring in baseball.

Using the Retrosheet game logs and umpire databases, I constructed a file of umpire careers. I found birthdays for only those umpires who worked for a minimum of 10 seasons from 1954 until the present. I would have preferred not to use the career-length cutoff, but the ages had to be entered by hand. Here are some basic stats.

Starting Age: 32
Retirement Age: 52

The data shows that umpires reach the majors in their early-to-mid thirties. I really don’t worry too much about MLB not selecting the best umpires to fill vacancies. Among those who rise to the top, MLB can evaluate and hire the best from that group. It’s who makes up the population from which MLB selects umpires that may be problematic. This means it’s important to understand how umpires make their way to the top.

Umpires begin their careers the minor leagues, where they earn extremely low wages. Minor league umpire salaries range from $1,800 to $3,400 a month, which translates to about $11,000 to $20,000 for six-months of games. I could hardly believe these numbers when I read them, because this is an extremely important age for acquiring skills that will be used for life.

The starting salary for major-league umpires is around $90,000 with top salaries maxing out around $350,000. While MLB umpires are certainly respectable, the probability of earning a big-league promotion are long. At low levels there are umpires covering games for over 200 teams, all vying for slots in the 30-team major league. Not only must you suffer through many years of low pay, but there exists the possibility that even if you excel and do everything right, there won’t be a spot for you when you rise to the top. Thus, the major-league salary probably isn’t high enough for most people to justify enduring the low-wage employment. This means there are two types of people who pursue umpiring as a career: those who love baseball so much that being in the game compensates for the low pay and people with low opportunity costs because they have few other valuable skills.

I suspect that the former group make up a larger pool of the labor supply, but the fact that most umpires don’t see the rewards until their mid-thirties means that the most competent umpires will be tempted to do other things. Maybe that’s not bad for society, because in the grand scheme of things baseball isn’t all that important, but it’s not good for encouraging the best umpires to stick around. Good umpires will have more opportunities outside of umpiring than bad umpires, and will be more likely to leave the profession.

But what happens when umpires make it to the majors? The histogram below plots the frequency of umpire career lengths since 1954.

The mean career length is 20 years, the median is 21 years. The histogram shows that about half of umpires work between 20 and 30 years, and that only 13% work less than 10 years. Basically, once you make it to the big leagues, you stay. This is where the dilemma of evaluating umpires comes in.

One of the things that may keep developing umpires in the minors to suffer low wages is the fact that they expect a 20-year paycheck that averages over $100,000 per year. While strict monitoring at the high levels will improve current umpiring, it also likely discourages future umpires from sticking it out in the minors. If MLB started whacking bad umpires, the expected value of the job will plummet. Certainly, umpires who stay in the game will be more careful in their umpiring, but the impact on the lower level cannot be ignored. Plus, if age takes away some of an umpire’s ability, no matter how hard an umpire works, his performance may decline when he is older to force an early retirement. This may explain why MLB has been reluctant to discipline bad umpires. While I’ve heard commentators blame the umpires union, MLB had no problem breaking it in 1999; which was no surprise given the dearth of available replacements.

Stable employment has value, especially in a field where there are few other options for your skills. If you are fired from your umpiring job at 40, what can you do? You’ve likely spent the past two decades doing nothing but umpiring when you could have been acquiring human capital in other areas. Going back to school or starting at the bottom of the employment ladder are difficult to do at that age. The promise of job security is a key motivator for developing umpires.

This relationship is similar to tenure for college professors. You spend years in school studying tangentially relevant topics in order to put young adults through mental gymnastics for a few years. After many years school, lecturing, and publishing research that is normally read only by three people (the author, editor, and a referee), losing your employment would be devastating. When you apply for jobs, you’re competing with young crop of new professors, who are much more attractive to employers because they are fresh out of top graduate schools where they have been working with the best minds in the field. Tenure is a cheap way to offset the risk of losing a job that has very few alternatives. It allows schools to pay professors relatively low wages, by offsetting the risk of termination.

But we all know the downside of tenure. The young energetic professor slowly transforms into a grumpy apathetic asshole who is late to class but early to receptions. It doesn’t mean that there are not good tenured professors—at least, I hope there are, because I’m in the cohort—but there exists an opportunity for shirking. On the margin, even the best professors shirk a little more than they did before tenure. Do we see this effect among baseball umpires?

Measuring umpire performance over time is more difficult than it is for players, whose performances can be measured objectively from widely-available data. While new technology makes it easier to evaluate umpires than it used to be, the data available to track umpires over a long time-period is more subjective—I can’t tell whether the performances are good or bad, only that they are different from their colleagues. I decided to compare umpires’ strikeout-to-walk ratios to the league average and see how they changed with age. If umpires shirk or become less competent with age, then we should see their K/BB deviations from the average increase over time. The reason I use the deviation from the average is to control for changes in league rules, policies, or informal changes that affect umpire ball-strike calls over time. From 1954–1999, umpires are compared to their own league; from 2000-2008, after the crews merged, they are compared to the major-league average.

Using a fixed-effects least-squares estimation technique that controls for individual umpire tendencies, I estimated the impact of age on the absolute percentage deviation of umpire strikeout-to-walk ratios from the league average over time.* It turns out that every year an umpire ages he increases his deviation from the league average by about 0.8%. That doesn’t seem like a lot—and it really isn’t a huge effect—but over a period of 12 years that pushes the umpire a full standard deviation (9.5%) above/below the average deviation. Thus, by the end of an umpire’s career, his calls are about two standard deviations from the typical deviation. This is evidence of a tenure effect or a loss of competency.

It’s also important to look at how consistent umpire calls are across individuals. The spread above takes into account that umpires have their own tendencies to call balls and strikes (due to the use of fixed effects). The age effect exacerbates any consistent deviation that an umpire has. Below, I list the average K/BB ratios for umpires with more than 300 games behind the plate from 1998–2008, ordered from highest to lowest.

How does the league allow Doug Eddings and Derryl Cousins to keep their jobs? Maybe one of them is enforcing the true strike zone (though, I doubt it), but both of them cannot be doing so—they are seven standard deviations apart. It’s clear that strike zones differ quite a bit by umpire, and this should not be the case. No wonder the umpires are worried about monitoring; they should be, because some of them are not properly enforcing the strike zone. The disparity across umpires also might help explain why veteran pitchers disliked Questec: they had amassed knowledge of umpire tendencies that gave them an advantage over hitters and younger pitchers.

Former commissioner Fay Vincent, who isn’t at all bitter that he was sacked by the owners, recently suggested that MLB should take over the training of umpires to improve umpiring. I don’t think this gets to the root of the problem. Private clinics that produce bad umpires will fail, good ones will succeed. Training is not the root of the problem and isn’t in need of an MLB subsidy.

Rather than spend more money training umpires, I’d urge MLB devote more resources to umpire salaries at all levels. This should be combined with increased monitoring that includes swift termination for bad umpiring. These policies should improve the talent pool from which MLB selects umpires and give existing umpires incentives to properly call the game.

I believe MLB could strengthen its objective rating of umpires through technology and human evaluation. MLB sets the rules of the game and is responsible for making sure that the rules are properly enforced. There is no excuse for the disparity in ball-strike calls across umpires. Doug Eddings should be told to get his calls in line with the rules—that is, unless he’s the lone umpire properly calling balls and strikes—or be fired.

But tighter monitoring cannot be the only step. Monitoring with stiff penalties generates a development problem unless the payoffs for becoming an umpire change. Umpires in the minors may give up working if they see that their expected tenures in MLB will be cut short. There is a simple fix to this problem: pay umpires more at all levels. Maybe even pay some of the bad ones to go away, just as universities do with shirking tenured professors.

At low levels, better compensation will mean more good talent will be attracted to umpiring as a profession, and a good umpire may be willing to stick around longer when his part-time winter employer offers him a raise to go full-time. Higher pay at the MLB level will keep good low-level umpires in the minors in hopes of a long-term payoff as well as increase the opportunity cost of being a bad umpire. Umpires will have an incentive work on improving their skills in order to earn their big paychecks. Overall, the effect of higher pay will permit MLB to fire bad umpires while doing less harm to the talent pool of potential umpires.

Addendum: I just noticed that the umpiring goats of this post-season, Phil Cuzzi and Tim McClelland, are near the top and bottom of the K/BB list.

*The estimate is statistically significant at the 1% level. The model included indicator variables to control for year effects, and I only looked at umpires in seasons when they covered at least 15 games behind the plate. The estimation includes a correction for detected first order serial correlation.

it’s time for a comprehensive study of whether there is a “Duncan Effect” on pitchers, like the one that JC Bradbury did on Leo Mazzone. Until then, no one knows for certain what kind of an impact (if any) Duncan has on pitchers.

Well, because you ask so nicely, I’d be happy to oblige. Actually, it’s easy because I already did the study.

Two years ago, Sports Illustrated asked me to look into the question, and I ran a study similar to the one I did for Leo Mazzone in The Baseball Economist. I looked at how pitchers performed with and without Duncan, controlling for factors such as age, parks, and pitcher quality. I found that Dave Duncan’s pitchers improved their ERAs by about 0.35 runs—yeah, he’s pretty darn good.

If you haven’t seen this before, it’s because the estimate buried on page 60 of the September 27, 2007 issue of SI in a story about Duncan and his sons. I meant to write about it at the time, but I never got around to it.

According to the 2010 Bill James Handbook, Kelly Johnson projects to hit .274/.354/.445. That sounds about right to me. It’s also better than Jeff Francoeur’s .276/.318/.437, but I still think the Mets wouldn’t have taken KJ for Ryan Church—their loss, our gain.

If you want to see some more projections, I have posted projections for all hitters and pitchers (with permission).

UPDATE: Sorry, if you came here looking for the file. A representative at ACTA publishing asked me to remove the link. I was told it was OK to post the file, but apparently they have changed their minds.
Hitter and Pitcher Projections from The Bill James Handbook 2010

I found this anecdote from Derrick Goold at the St. Louis Post-Dispatch to be curious.

What age is too aged to be a prospect?

There is no real answer.

The St. Louis Cardinals, as described by farm director Jeff Luhnow, have studied how high-end players — the top-notch, elite, standout prospects — reach the majors in their early 20s, and how they excel because of that. Colby Rasmus, who was 22 for most of this last season (his rookie season), fits that model. That trend, Luhnow has said before, is part of the reason why the organization adopted a more aggressive promotion approach a few seasons ago, and why young players Eduardo Sanchez, Richard Castillo, Daryl Jones and a few others were pushed up a level. Even some of the Cardinals’ international signings have been hastened into a short-season club to see how well they adjust a more demanding level.

So, the Cardinals have noticed that elite players tend to reach the majors in their early twenties; thus, they are promoting prospects quickly in order to increase their chances of becoming elite players? I cannot believe that Jeff Luhnow actually believes this, at least not for the reason listed above. Of course, better players hit the majors at an age younger than most players. This is because their inherent talent allows them to be good enough to play at the major-league level earlier in their development than most other players. Simply moving a player along to the next level doesn’t make him better; in fact, I suspect it stunts growth when players struggle after being promoted too early.

I have nothing against promoting players who are ready to move up to the next level—and I hope that the Cardinals believe that promotions should only occur after meeting predetermined benchmarks—but I think it is highly unlikely that moving up causes a player to be better.

Looking at the performances of the prospects mentioned above, I don’t see much evidence of success from pushing prospects.

Eduardo Sanchez was promoted to double-A after blowing away high-A for only 25 innings. While this may seem quick, he did follow up on a nice 2008 season in low-A ball, so the promotion is not a total shock.

After playing in the Venezuela Summer League at 17, Richard Castillo started at high-A in 2008. But after 16 innings of decent, but not fantastic play—it’s hard to tell in so few innings—he was sent to low-A to finish out the season. He spent all of 2009 in high-A, pitching decent but not spectacular ball.

Daryl Jones was promoted to high-A in 2008 after a good season in low-A. He played well in high-A for the remainder of the year. He repeated high-A in 2009, and his performance wasn’t so hot.

And then there is Colby Rasmus, who followed up poor showing in triple-A with a stinker of a rookie season.

The fact that elite players hit the majors sooner than other players doesn’t mean their quick ascensions caused this. Ryan Howard and Wade Boggs were not worse for being held back. After watching the Braves push Kyle Davies and Jeff Francoeur, I believe it is best to wait too long. These guys are professional athletes who must have big egos to succeed. When things don’t go well, development may be damaged by taking short-cuts. I could be wrong. I can’t prove that Davies and Francoeur would be much better players if they had been held back any more than I can prove that Boggs and Howard excelled because they stayed in the minors longer. But, what damage does it do to let these guys play their way to the next level?

So, in answer to the question “What age is too aged to be a prospect?” It depends. The younger the player for his level, and the better the performance, the more likely it is that he will succeed. Bumping a player up to make him better is not a strategy that I advocate.

That’s the question that Mets blogger James Kannengieser asks. Not too long ago it’s a question that the Braves were facing, but now it’s the Mets problem (boy, it feels good to write that). At the time, I generated some estimates of Francoeur’s worth that projected he was worth around $12 million, and should expect around $3 million in an arbitration award. Understandably, this upset some people (including me) for the sake of the sheer size of the number. Now that the question of Francoeur’s worth is relevant again, I want to revisit the question.

Let me first begin by stating that my initial estimate was too high—way too high. I was giving credit for non-marginal revenue contributions and over-weighting defense. I’ve spent much of the past year tearing down and rebuilding my system for valuing players for a book project on valuing players. Though I have corrected the model, the foundation of the model is still the same. I use team revenues to estimate the value of winning, estimate player contributions to winning, and then impute player marginal revenue products (MRPs) from these estimates.

In 2009—including his awful time with the Braves, and his good stint with the Mets—I estimate that he was worth $6.8 million. Arbitration-eligible position players tend to earn approximately 74% less than their MRP estimates; thus, in arbitration Francoeur might expect to receive around
$1.8 million. That’s $1.6 million less that his 2009 salary. Even if the Mets are able to successfully convince an arbitrator that Francoeur is worth $1.8 million, the Collective Bargaining Agreement limits the salary reduction to 20%: $2.7 million. But, that’s not relevant to the Mets. Sure, they wish he hadn’t been signed to a bigger deal. The question is: is he worth $2.7 million?

The $6.8 million estimate says he’s worth well more than that, but the estimate is misleading. The MRP estimates give credit for the playing time, and Francoeur’s managers have played him far too much. A lot has been made of Francoeur’s dismal 2008 and 2009 with the Braves. Just as he was never as good as his 2005 rookie campaign nor his 2009 stint with the Mets, I don’t believe Francouer was that bad. For his career, Francoeur has an OPS of .743, his career OPS+ of 92 is equal to his overall 2009 performance. He’s no Natural, but he is a useful player who can serve in a platoon/reserve role. But, that’s not how the Braves or the Mets used him. Since his first full season in the majors he’s averaged 666 plate appearance a year. While this number may be appropriate for the anti-Christ, it’s not the number of PAs that any manager should be giving Jeff Francoeur. Jeff Francoeur should probably play 50% of what he has played, cutting his MRP estimate in half. With that in mind, Jeff Francouer is really a $3–$4 million player, depending on how good he really is. The good news for my estimates is that managers have strong incentives not to make such mistakes when filling out their line-up cards; but because they do, it’s important to interpret the raw estimates with care.

If the Mets non-tender Francoeur, they will likely end up having to spend about what they are paying him to replace him on the free agent market. Given that he seems to be popular with fans, media, and players; it’s probably worth keeping him around at that price, even if he ends up winning an arbitration award similar to this season’s salary. If he has a bad year, you cut him loose. If he has a good year, then you can take him to arbitration one more year, maybe even sign him to a long-run deal. Non-tendering him wouldn’t be the worst thing in the world, and given the hold he seems to have on his managers, it might be best to not give his skipper the opportunity to put him in the line-up. The one thing that I would not recommend is signing him to a long-run deal now. What’s the rush? The worst thing that happens by not going long-term is that he has a good season and he gets a deserved raise in arbitration. And if Francoeur is desperate to sign a long-run deal—as he was hinting at the end of the season—then that is probably an indication that he doesn’t think he’s going to get much better either.

As a follow-up to my little clutch hitting study, I thought it would be interesting to look at clutch pitching using the same methodology. Though I don’t believe there is good reason to expect clutch performance among hitters, I think it’s plausible that pitchers may have some clutch skill. Pitchers have to regulate their effort throughout the game and often change the way they pitch with runners on base (employing the stretch). Theses factors leave room for pitchers to perform differently when the stakes of the game change. Pitching better with runners in scoring position (RISP) may not be “clutch” in the Platonic sense of rising to the occasion, but it’s a skill worthy of examination.

I looked at individual RISP plate appearances in 1992 and estimated the impact of past clutch performance controlling for the overall pitcher performance in each area (allowed AVG, OBP, SLG, strikeout rate, walk rate, home run rate), the skill of the batter in each area, and the platoon effect (platoon = 1; 0 = otherwise). I used RISP performance in 1989–1991 to proxy clutch ability—if pitchers have clutch skill, past clutch performance should correlate with present clutch performance.

The table below lists the coefficients (reported as marginal effects) and robust z-statistics of regression estimates in seven performance areas. I used the probit method to estimate binary outcomes (outcome = 1 if an event occurred, and 0 otherwise) of individual plate appearances for hits, on-base (hits + walks + hbp), strikeouts, walks, non-intentional walks, and home runs. I used the negative binomial method to estimate the impact of the variables on the number of total bases resulting from a plate appearance.

Past RISP performance is not a statistically significant predictor of 1992 RISP performance. Walk rate appears to be an exception—with pitchers consistently performing worse with runners on base (and having a z-stat > 2)—but the higher probability of walks seems to be caused by the increase in intentional walks issued with the hope of turn out a double play. When IBBs are removed, pitcher RISP walk performance loses its statistical significance.

The results do hide one thing: pitchers perform better in RISP than non-RISP situations, except when walks are involved. The table below shows the average of outcomes for all events. All differences are statistically significant.

The numbers remove intentional walks, therefore the worse performance in preventing walks, which also shows up for on-base probability, could represent “intentional unintentional-walks” or pitchers losing control a bit when runners are in scoring position. But if the latter were true, I would expect the numbers to be worse in the other areas. Also, because the numbers below are the percentages of all outcomes, the better numbers in RISP may also reflect better relievers entering the game for such situations.

The main story here is that the regression estimates indicate that after controlling for several relevant factors pitchers don’t appear to have any special skill over other pitchers in performing in RSIP situations. A pitcher’s overall performance level does a fine just of predicting performance, and knowing past clutch performance doesn’t appear to add useful information.

Valuing Hudson is a bit difficult, because of his recent past performance. He pitched well in 2007, but his 2006 and 2008 seasons weren’t as good—the latter season was marred by injury. Let’s just assume that 2007 was Hudson’s true-talent level. Given aging and league salary growth, I project Hudson will be worth $11.25 million in 2010. The Braves having an above-average team pushes this value upward a bit, but slower-than-normal revenue growth would lower the value. In addition, injury recovery isn’t guaranteed, which makes him riskier than I have assumed in this analysis.

By the rosiest of scenarios, Hudson will be worth the option. Given the dearth of pitching already owned by the Braves, and the possibility of a weak free-agent market (Update: by weak, I mean talent will be cheaper than usual, not weak in talent), I suspect that the Braves will pass on Hudson’s option.

In summary, I don’t think Hudson can get more than $12 million/year on the free agent market. Maybe, this is posturing: leaked position by Hudson’s agent as a negotiating ploy. Or, if you’re going to be fired, quit first to save face. Most likely, I think Hudson would prefer a long-term deal with another team for less that $12 million a year, and the Braves aren’t willing to offer a favorable long-term deal. Therefore, he’s willing to trade a one-shot above-market deal for a long-run market-equivalent deal.

One thing that I do not think affects Hudson’s value is the available number of starting pitchers on the free agent market. While there are fewer players for teams to choose from (decreased supply), this also means there are fewer teams seeking starters (decreased demand).

I’ve been getting a few hits for the term “productive outs” lately. I blame TBS (so does Steve Goldman). When the stat came into being five years ago, I did a little study of its impact, and I thought I’d repost my findings.

If there is anything of use in POP it must be in addition to the impact of OBP and SLG, not an alternative measure. Olney’s argument ought to be: all else being equal, teams that have a higher percentage of productive outs will score more runs than those that do not. This means that when two teams have identical OPSs the one with a higher POP will score more runs. So, what happens when I run a regression including both OPS and POP, which allows me to control for the run-scoring abilities of teams due to OBP and SLG, to capture any additional POP effect? Well, not much. Using the 2004 team data provided by ESPN.com I find that POP has no effect on run-scoring. Though the coefficient is negative it is not statistically significant.

So, why doesn’t it have an effect? I mean, clearly logic dictates that productive outs are preferred to non-productive outs. The problems lies in the fact that productive out situations are also productive at-bat situations. While productive outs are preferred to non-productive outs, non-outs are even better. A team that is producing productive outs is still producing outs.